1. Field of the Invention
The present invention relates to a navigation apparatus and a map matching method. More particularly, the invention relates to a navigation apparatus that displays a map covering a vehicle position and its surroundings on a display device using map information, while displaying a mark indicative of the vehicle position on the map, and a map matching method.
2. Description of the Related Art
A navigation apparatus is designed to read map data corresponding to a present position of a vehicle from a map data storage section, such as a DVD or a HDD, and to draw the data read on a display screen, while moving a mark indicative of the vehicle position on the map according to travel of the vehicle, or while scrolling the map with the vehicle mark fixed in a set position (for example, in a center position of the display screen) on the screen.
The map data comprises (1) a road layer including node data, road link data, intersection data, and the like, (2) a background layer for displaying objects on the map, and (3) a character layer for displaying names of a city, a town, and a village and the like. A map image displayed on the display screen is generated based on the background layer and the character layer, whereas map matching processing and guidance-route search processing are performed based on the road layer.
In such a navigation apparatus, it is essential to measure a present vehicle position. Some measurement methods of the vehicle position have historically been put into practical use, for example, a measurement method for measuring the vehicle position using a distance sensor and an angle sensor (gyro) mounted on the vehicle (which is the so-called “autonomous navigation method”), a measurement method performed by a global positioning system (GPS) using satellite (which is the so-called “satellite navigation method”), and a measurement method using the combination of the above-mentioned methods.
In particular, the recent vehicle navigation apparatus makes use of the combination of the autonomous navigation and the satellite navigation methods. The navigation apparatus normally estimates or measures a position and an azimuth of the vehicle using the autonomous navigation method. Then, it modifies the measured or estimated vehicle position by map matching processing to determine a real vehicle position on a travel road of the map. If the map matching performed by a pattern matching method becomes impossible, the map matching processing is initialized, and a position measured by the GPS is set as the vehicle position at that time. Thereafter, the position and azimuth or heading of the vehicle are estimated again by the autonomous navigation method, and the map matching processing is restarted to match the estimated vehicle position to the real position on the map travel route.
In the autonomous navigation method, the vehicle position may be calculated by the following integration based on outputs from the distance sensor and the relative direction sensor. FIG. 7 is a diagram explaining a method of detecting a vehicle position using the autonomous navigation method. The distance sensor outputs a pulse every time the vehicle travels a unit distance L0 (for example, 10 m). A reference azimuth (θ=0) corresponds to a normal direction of the X axis. A counterclockwise direction relative to the reference azimuth is set as a positive direction, namely, + direction. A previous position of the vehicle is denoted as a point P0(X0, Y0), and an absolute azimuth of the vehicle travel direction or heading at a point P0 is set as θ0. An output from the relative direction sensor at a time when the vehicle travels the unit distance L0 is Δθ1. A change in the vehicle position will be calculated from the following equation.ΔX=L0·cos(θ0+Δθ1)ΔY=L0·sin(θ0+Δθ1)
Further, an estimated azimuth θ1 of the heading of the vehicle at a present point P1, and an estimated vehicle position (X1, Y1) can be calculated by the following vector sum:θ1=θ0+Δθ1  (1)X1=X0+ΔX=X0+L0·cos θ1  (2)Y1=Y0+ΔY=Y0+L0·sin θ1  (3)
Accordingly, once the absolute azimuth of the vehicle and coordinates of the position thereof at a starting point are specified by the GPS, then the vehicle position can be determined (estimated) in real time by repeatedly calculating the above-mentioned equations (1) to (3) every time the vehicle travels the unit distance.
In the autonomous navigation method, however, error accumulates over the course of the vehicle travel to cause the estimated vehicle position to deviate from a road or route. Then, the map matching processing is performed to verify the estimated vehicle position against the road data so as to match the estimated position to the real vehicle position on the map route.
FIG. 8 is a diagram explaining map matching using a projective method. The present vehicle position is set as a point Pi-1(Xi-1, Yi-1), and a vehicle azimuth as θi-1. (In the figure, the position Pi-1 is not located on a road RDa). When the vehicle travels a fixed distance L0 (e.g. 10 m) from the point Pi-1, a vehicle position Pi′(Xi′, Yi′) estimated by the autonomous navigation and an estimated vehicle azimuth θ at the point Pi′ may be determined by the following equation wherein Δθi is a relative azimuth:θi=θi-1+Δθi Xi′=Xi-1+L0·cos θi Yi′=Yi-1+L0·sin θi 
At this time, a link (serving as an element constituting a road) may be searched for which is located in a 200-square-meter area with the estimated vehicle position Pi′ positioned in the center thereof, wherein a perpendicular line is dropped from the link, an angle between a line with an estimated azimuth of the vehicle θi at the vehicle position Pi′ and the link is within a predetermined range (for example, not more than 450), and a length of the perpendicular line dropped from the position Pi′ to the link is not more than a predetermined value (for example, 100 m). This may result in a link LKa1 with an azimuth θa1 on a road RDa (which is a line connecting nodes Na0 and Na1), and a link LKb1 with an azimuth θb1 on a road RDb (which is a line connecting nodes Nb0 and Nb1).
Then, lengths of perpendicular lines RLia and RLib dropped from the estimated vehicle position Pi′ on the links LKa1 and LKb1 may be determined. Thereafter, coefficients Z may be calculated by the following equations:Z=dL·20+dθ·20(dθ≦250)  (4)Z=dL·20+dθ·40(dθ>250)  (4)′where dL is a length of the perpendicular line dropped from the estimated vehicle position Pi′ onto the link (that is, a distance between the estimated position and the link), and dθ is an angle between the estimated vehicle azimuth θi and the link. The larger the angle dθ, the larger the weight coefficient.
After the coefficient Z is determined, a link satisfying the following conditions 1) to 3) is selected which has the smallest value of coefficient Z as a matching candidate (optimal road), which is hereinafter referred to as a LKa1.
1) distance dL≦75 m (maximum drawing distance 75 m)
2) angular difference dθ≦300 (maximum drawing angle 300)
3) coefficient value Z≦1500
A travel locus SHi connecting the point Pi−1 and the point Pi′ is moved in parallel toward the perpendicular line RLia until the point Pi−1 is superimposed on the link LKa1 (or on an extended line from the link LKa1) to determine moved points PTi−1 and Pti′ which correspond to the points Pi−1 and Pi′, respectively. (f) Last, the point PTi′ is rotated around the point PTi−1 until it reaches the link LKa1 (or an extended line from the link LKa1) to determine a point after rotation, which is the real vehicle position Pi(Xi, Yi). Note that the heading of the vehicle at the real position Pi remains θi. Alternatively, when the point Pi−1, which is the previous vehicle position, is located on the road RDa as shown in FIG. 9, the moved point PTi−1 is identical to the point Pi−1.
For example, in a section where a highway HWY and a general road GRD are lied in parallel in a vertical stereostructure as shown in FIG. 10(A), and at an interchange where there are interchange roads RD1 and RD2 and a side road SRD leading from the lower road to the upper road as shown in FIG. 10(B), the measured vehicle position may happen, by mistake, to be matched onto the map road where the vehicle does not actually travel.
Thus, conventionally, information for specifying a gradient of a road link (upgrade, downgrade, or flat) is incorporated into the map database as disclosed in JP-A-10-253373. A gradient of the road link being presently traveled, that is, whether the road link is an upgrade or a downgrade, is detected using an acceleration outputted from an acceleration sensor. The gradient of the road link being traveled is verified against the link gradient information incorporated into the map information to perform the map matching processing without error even in the cases as shown in FIGS. 10(A) and 10(B).
For example, in cases where the general road GRD runs parallel to the highway HWY as shown in FIG. 11, when the vehicle is descending from an A point on the highway into the general road GRD through a ramp RMP, it is detected using an output from the acceleration sensor that the road link (ramp RMP) being currently traveled is a downgrade. In the map matching, the vehicle position is matched or drawn onto the downgrade ramp RMP of the map route, and then onto the general road GRD positioned thereunder.
In the conventional map matching processing using the acceleration sensor, an angle of inclination of the travel road is measured, and if the inclination angle measured is above a set angle, it is determined that the vehicle is currently traveling an upgrade link or a downgrade link.
The inclination angle is calculated using an acceleration outputted from the acceleration sensor and a derivative value (acceleration) of an instantaneous speed determined from a speed pulse. The acceleration outputted from the acceleration sensor fluctuates when the vehicle stops or starts. FIG. 12(B) is a diagram showing an output waveform of the acceleration sensor while the vehicle starts from a position A, descends a downgrade ramp RMP as shown in FIG. 12(A), stops at a position B, and then starts traveling again. As can be seen from the figure, the output from the acceleration sensor includes error caused by a swing back effect or the like due to the start or stop of the vehicle. This causes the wrong determination of gradient when the acceleration outputted from the acceleration sensor is verified against the gradient information stored in the map database.
In the conventional map matching processing using the acceleration sensor, an angle of inclination of the road being traveled is measured, and if the inclination angle measured is above a set angle, it is determined that the vehicle is currently traveling an upgrade link or a downgrade link. In the prior art, a road link sloping gently over a long distance with an inclination angle of the set angle or less cannot be judged correctly as an upgrade link or a downgrade link, which may lead to the wrong map matching processing.
Additionally, in the prior art, a road link including a steep slant and a flat part following the slant have not been judged correctly as the downgrade or upgrade link. This disadvantageously results in the wrong map matching.